ESG controversies and investor trading behavior in the Korean market

Jeongseok Bang, Doojin Ryu*, Jinyoung Yu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

20 Citations (Scopus)

Abstract

This study examines how investor trading behavior changes following environmental, social, and governance (ESG) controversies by analyzing textual news data. We use deep-learning-based natural language processing to classify news articles into specific categories of controversy. ESG controversies generally increase investors’ trading activities regardless of their type, while their reactions differ by ESG pillar. Interestingly, domestic institutions tend to sell stocks with controversies.

Original languageEnglish
Article number103750
JournalFinance Research Letters
Volume54
DOIs
Publication statusPublished - Jun 2023
Externally publishedYes

Keywords

  • ESG
  • Institutional investor
  • Investor trading behavior
  • Natural language processing

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